AI Credits

Every plan in Relay.app comes with a generous number of free AI credits. AI credits are a single pool of credits that are consumed when running steps that use AI-related features, including:

  • Prompting AI models

  • Audio transcription and text-to-speech

  • Website scraping

The free AI credits that come with all our subscriptions are good for reasonable usage—see the tables below for more details and examples.

If you run out of AI credits in Relay.app, purchase more in your billing settings, or contact support@relay.app for help. Alternatively, if you already pay for credits with a AI service provider, connect that account to Relay.app and switch your AI automations to use that connected model.

Free monthly AI credits per plan

Plan
Free AI credits per month

Free

500

Professional

5000

Team

5000

When the AI credits included in your plan aren't enough, it's easy to add more via the billing page. Note that you need to be on a paid plan in order to be able to add additional AI credits. If you're on a Free plan, upgrade to Professional or Team first.

What can I do with 1 AI Credit?

It depends! Different models and operations require different numbers of credits. A detailed conversion table is below, but here some concrete examples:

  • Summarizing an email will typically uses about 1 AI Credit (but may be much less)

  • Scraping text from a website uses about 5 AI Credits

  • Transcribing a minute of audio uses about 10 AI Credits

AI Credits conversion chart

Updated: 2025-02-10

AI Model / tool
1 AI credit is consumed for every...

Web scraping: general

-> 5 AI credits per website scraped

Web scraping: Google Search

-> 5 AI credits per Google Search performed

Web scraping: Amazon, Zillow, Indeed

-> 1.67 AI credits per number of Profiles/Pages requested

Web scraping: LinkedIn

-> 7 AI credits per request

OpenAI Audio Transcription

6s of transcribed audio

OpenAI Text-to-Speech (TTS)

Fast: 40 characters converted to speech High definition: 20 characters converted to speech

DALL-E 3 image generation

-> 14 AI credits per image

Anthropic Claude 3 Haiku

480 output tokens

2400 input tokens

Anthropic Claude 3.5 Haiku

120 output tokens

600 input tokens

Anthropic Claude 3 Opus

8 output tokens

40 input tokens

Anthropic Claude 3.5 Sonnet

40 output tokens

200 input tokens

Google Gemini 1.5 Flash

<128k context:

2k output tokens

8k input tokens >128k context: 1k output tokens 4k input tokens

Google Gemini 2.0 Flash Lite Preview

2k output tokens 8k input tokens

Google Gemini 2.0 Flash

1.5k output tokens

6k input tokens

Google Gemini 1.5 Pro

<128k context:

120 output tokens

480 input tokens >128k context: 60 output tokens

240 input tokens

OpenAI GPT-4o mini

1k output tokens 4k input tokens

OpenAI GPT-4o

60 output tokens 240 input tokens

OpenAI o1

10 output tokens 40 input tokens

OpenAI o3-mini

50 output tokens 200 input tokens

Perplexity Sonar Reasoning

120 output tokens 600 input tokens

Perplexity Sonar

600 output tokens 600 input tokens

Perplexity Sonar Pro

40 output tokens 200 input tokens

DeepSeek V3

500 output tokens 2k input tokens

DeepSeek R1

270 output tokens 1090 input tokens

Track your AI credit usage

Overall usage

To see how many AI credits your workspace has used this period and when they refresh, look at the widget on the bottom of the left-nav menu or in your billing settings.

Usage per step

Click on any completed step in a run to see how many credits it consumed when it ran.

About tokens

The definition of a token differs slightly by model provider. Additionally, input and output tokens are also differentiated from a cost/consumption perspective. We suggest reading the short FAQs from each model provider to learn more:

Unfortunately, it's not trivial to predict how many tokens an AI step will consume upfront, although the articles linked above will give you a better understanding.

For AI steps in Relay.app, token usage is primarily influenced by these factors:

  • Context included in the prompt The more and larger the attached context, the more tokens will be used every time your step is executed. For example:

    • An email can easily increase token usage by a few thousand

    • A PDF can go way beyond that, depending on the size

  • Whether the step is given Internet access All text on the websites that the model needs to visit for your prompt is included as context, including user-hidden HTML. This can be anywhere between a few hundred to tens of thousands of tokens used per step execution, depending on how many websites the model needs to visit and how large they are.

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